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scipy.stats.foldcauchy () is a folded continuous Cauchy random variable that is defined in a standard format and with some shape parameters to complete its specification.
Parameters:
- & gt; q: lower and upper tail probability
- & gt; a: shape parameters
- & gt; x: quantiles
- & gt; loc: [optional] location parameter. Default = 0
- & gt; scale: [optional] scale parameter. Default = 1
- & gt; size: [tuple of ints, optional] shape or random variates.
- & gt; moments: [optional] composed of letters [’mvsk’]; ’m’ = mean, ’v’ = variance, ’s’ = Fisher’s skew and ’k’ = Fisher’s kurtosis. (default = ’mv’).Results: folded Cauchy continuous random variable
Code # 1: Create a folded Cauchy continuous random variable Cauchy random variable
| < p> print ( "RV:" , rv) |
Exit:
RV: & lt; scipy.stats._distn_infrastructure.rv_frozen object at 0x0000018D55D8E160 & gt;
Code # 2: the folded Cauchy random variables and the probability distribution function.
import numpy as np quantile = np.arange ( 0.01 , 1 , 0.1 )
# Random Variants R = foldcauchy.rvs (a, scale = 2 , size = 10 ) print ( "Random Variates:" , R)
# PDF R = foldcauchy.pdf (a, quantile, loc = 0 , scale = 1 ) print ( "Probability Distribution:" , R)
Output:
Random Variates: [1.7445128 2.82630984 0.81871044 5.19668279 7.81537565 1.67855736 3.35417067 0.13838753 1.29145462 1.90601065] Probability Distribution: [0.42727064 0.42832192 0.43080143 0.43385803 0.43622229 0.43639823 0.4 3294602 0.42480391 0.41154712 0.3934792]
Code # 3: Graphic representation.
import numpy as np import matplotlib.pyplot as plt distribution = np.linspace ( 0 , np.minimum (rv.dist. b, 3 )) print ( "Distribution:" , distribution) plot = plt.plot (distributio n, rv.pdf (distribution))
Output:
Distribution: [0. 0.06122449 0.12244898 0.18367347 0.24489796 0.30612245 0.36734694 0.42857143 0.48979592 0.55102041 0.6122449 0.67346939 0.73469388 0.79591837 0.85714286 0.91836735 0.97959184 1.04081633 1.10204082 1.16326531 1.2244898 1.28571429 1.34693878 1.40816327 1.46938776 1.53061224 1.59183673 1.65306122 1.71428571 1.7755102 1.83673469 1.89795918 1.95918367 2.02040816 2.08163265 2.14285714 2.20408163 2.26530612 2.32653061 2.3877551 2.44897959 2.51020408 2.57142857 2.63265306 2.69387755 2.75510204 2.81632653 2.87755102 2.93877551 3. ]
Code # 4: Various Positional Arguments
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Output: 
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California | 2023-01-27
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Berlin | 2023-01-27
Maybe there are another answers? What scipy stats.foldcauchy () | python exactly means?. Will use it in my bachelor thesis
Abu Dhabi | 2023-01-27
I was preparing for my coding interview, thanks for clarifying this - scipy stats.foldcauchy () | python in Python is not the simplest one. Will get back tomorrow with feedback
